相关实验视频
Updated: Jun 25, 2025

12:44
Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
8.0K
在北美降水预测的不确定性减少
Dan Lou1, Wouter R Berghuijs2, Waheed Ullah3
1Nanjing Nriet Industrial Co., Ltd., Nanjing, China.
PloS one
|May 22, 2024
概括
北美未来降水预测被气候模型高估了. 一个新出现的约束表明,结合历史温度趋势可以缩小不确定性,并纠正降水和蒸发估计.
科学领域:
- 气候建模和气候预测.
- 大气科学和陆地-大气相互作用.
背景情况:
- 在27个合模型对比项目第6阶段 (CMIP6) 模型和四个排放场景中,北美预计降水增加存在重大差异.
- 这些变化部分归因于当前气候模型中对陆地-大气相互作用的不充分表示.
研究的目的:
- 建立一个新出现的约束关系,将未来降水增长率与历史温度趋势联系起来.
- 通过整合观察到的变暖数据来完善北美CMIP6降水预测.
- 评估现有模型预测的温度和蒸发速度的潜在高估.
主要方法:
- 根据年降水增长率与历史温度增长率之间的关系,开发出了一个新出现的约束.
- 应用观察到的变暖趋势来调整四个共享社会经济路径 (SSP) 的原始CMIP6降水预测.
- 量化了限制后降水预测不确定性 (标准偏差) 的减少.
主要成果:
- 限制性CMIP6预测显示,未来每十年降水增加的幅度较低:0.40-0.48% (SSP126),0.83-0.93% (SSP245),1.29-1.45% (SSP370) 和1.70-1.87% (SSP585). 在过去的十年中,降水增加的幅度较小.
- 新出现的约束使预测不确定性减少了13.8-31.1%.
- 与受约束结果相比,原来的CMIP6模型高估了年度温度上升 (6.0-13.2%) 和总蒸发 (4.8-14.5%).
结论:
- 来自CMIP6模型的北美未来降水预测可能被高估了.
- 温度在准确的气候预测中起着至关重要的作用,突出了当前模型模拟中的系统错误.
- 该研究强调了改进气候模型中的陆地-大气相互作用和温度表示的重要性.
相关概念视频
Precipitation and Co-precipitation
1.8K
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
1.8K
Precipitation Processes
446
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
446
Precipitation Gravimetry
6.1K
Precipitation gravimetry is based on converting an analyte into a sparingly soluble precipitate, which is separated by filtration and weighed. An ideal precipitate should be pure, insoluble, of known composition, and easily filtered from the reaction mixture.
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
In determining nickel by gravimetric analysis, a precipitant of ethanolic dimethylglyoxime is added to a hot nickel salt solution. This is quickly followed by the dropwise addition of dilute ammonia solution until precipitation occurs. A...
6.1K
Propagation of Uncertainty from Random Error
680
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
680
Propagation of Uncertainty from Systematic Error
516
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
516
Uncertainty: Confidence Intervals
4.1K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
4.1K

